Methods and apparatuses for pre-action gaming

ABSTRACT

Aspects of the disclosure include methods and apparatuses for pre-action gaming. For example, in an aspect, a method is presented for constructing a user-controllable image, comprising obtaining anatomical and physiological data associated with a body, storing the anatomical and physiological data in a database; and creating the user-controllable image based on the stored anatomical and physiological data, wherein the user-controllable image is configurable to a user, wherein at least a moveable portion of the user-controllable image is constructed to move based on input from a user, and wherein the user-controllable image is constructed so as to enable pre-action training the user. As such, victims of traumatic brain injury or other neurological setbacks may pre-train their nervous system for use of one or more injured body parts.

CLAIM OF PRIORITY

The present application claims priority under 35 U.S.C. §119 to U.S.Provisional Application No. 61/665,221, entitled “Methods and Apparatusfor Pre-Action Gaming,” and filed on Jun. 27, 2012, which isincorporated herein by reference.

TECHNICAL FIELD

Embodiments pertain to the field of user self-teaching pre-action gamingsimulations, synonymously, pre-action training, pre-action exercise, orinstantiating kinetic imagery in virtual environments. The presentdisclosure further relates to constructing, configuring, or controllinguser controllable images as used in pre-action training. The presentdisclosure further relates to methods and apparatus that provide foruser pre-action training control of non-virtual prostheses, exoskeletonbody parts, robots or other motile or audiovisual devices.

The broad medical problem is that while training simulations areubiquitous, including extensive use for training health care providers,the individuals most in need in of care e.g. patients, survivors andother health-affected individuals (synonymously “users”) have few, ifany, simulations tailored to their needs and none in said field. Saidusers' goals may include regaining or improving processes that enableperforming activities of unaffected living after, without limitation:neurological injury or condition resulting from penetrating ornon-penetrating insult injury or stress; or physical injury due toinvasive or non-invasive causation; or experiencing psychological orneurochemical disorder. The economic problem is that said users undergolong-term and costly therapeutic and rehabilitative procedures thereforeconsuming significant healthcare services and costs without recourse toheuristic health improvement methods and apparatuses. The access-to-careproblem is that when affected by an injury, condition, or disorder,there are insufficient methods and apparatuses to activate needed brainprocesses, or to stimulate, much less repeatedly stimulate, withoutlimitation, neurons, neurological support cells, inter-neuroncommunications, gray and white matter cortical circuitry, other braincircuits or communications or tissues or proteins of the brain orcentral nervous system. The user's more particular medical, therapeutic,and rehabilitative care problems are to use said method and apparatus atleast to improve the neurological, physical, or psychological conditionsnoted above.

Further, the said user's medical therapeutic and rehabilitative careproblems are access to diagnoses or measurements or biomarkers of brainprocesses or activations, or determinations of amounts or levels ofbiological substances, without limitation, tau proteins. One solution tosaid users' problems in preparing for real-world physical actions is touse methods and apparatuses for pre-action control of user-controllableimages that enable user pre-action training control of non-virtualrobotic, prosthetic, and exoskeleton objects. One objective is toprovide a method and apparatus enabling said user to instantiate kineticimagery using simulations i.e. to transition from personal mental imagesor visualizations of physical actions into instantiations of simulatedphysical actions, synonymously, “viewable embodiments of corticalsimulations of physical actions.” One technical problem therefore is toconstruct user controllable images that are anatomically realistic, haveanalogous true range of motion, are user controllable to simulatephysical actions on any display screen and thereby to provide said userwith stimulating virtual alternatives to actual physical actionfeedback. The applicants' self-training gaming simulations-improvementproblem is to measure or ascertain brain activity and biologicalsubstances and, based on that information, to improve said pre-actiongaming simulations to enhance user objectives or improve userconditions.

BACKGROUND

The present invention enables negatively health-affected individualse.g. said users, synonymously, “plurality of users,” to useself-controlled and/or directed pre-action training simulations tostimulate brain structures and processes. Operationally, said usercontrols virtual body parts that are anatomically realistic withanalogous true range of motion to simulate physical actions, therebyengaging in pre-action gaming simulations. Said invention enables saiduser to repeat brain stimulation in part through interactiveinstantiation of kinetic imagery, synonymously, “viewable embodiments ofcortical simulations of physical actions.” The invention is directedwithout limitation to individuals affected by stroke, traumatic braininjury, focal dystonias, chronic traumatic encephalopathy, amputees,joint replacement patients, or other conditions in need of physical,occupational or psychological rehabilitation/therapy, withoutlimitation, brain tumors, cerebral palsy, Parkinson's disease, autismspectrum disorders, schizophrenia, phobias, other acquired braininjuries (“ABI”), or other medical deficits, disorders or diseases.

Further operationally, before or without being able to perform physicalaction(s), said user executes inputs (using any input device e.g.without limitation a computer mouse, touch-screen, head or eye actionsor wireless signals) that control/direct simulated physical actions ofon-screen images. Said user's physical method of inputs is physicallynon-corresponding to displayed actions of on-screen images. Said inputscontrol virtual body parts, synonymously, “the entire body,” whetherclothed, skin-covered, or exposed, displayed in any virtual environment.Said user inputs may simultaneously or sequentially control single ormultiple virtual body parts.

Physiologically, the user's challenge is to initiate or improve physicalor related cognitive actions before or without being able to perform orpractice said actions. The present invention can be used forself-teaching, without limitation: a) brain processes to enableperforming new actions or improve past actions e.g. to help stroke ortraumatic brain injury or chronic traumatic encephalopathy patients; orb) potentiation of brain processes to replace or supplement damagedneural circuits e.g. help joint-replacement patients regain abilities;or c) de-activation of existing neuromuscular actions, e.g. to decreaseor stop users' uncontrolled muscle contractions as in focal cervicaldystonia; or d) de-sensitization of damaged neural circuits e.g. phantomlimb or other painful body parts; or e) creation of brain processes tosupplant dysfunctional/debilitating experiences e.g. suffering fromphobias, schizophrenic hallucinations or autism spectrum sensory-actiondisorders.

For individuals with disabled or dysfunctional use of body parts or withpsychological conditions impeding control of actions or relatedcognitive processes, imagined action alone results in imagined feedback.Visualization and imagery alone, e.g. without creating pre-actionsimulations, are only somewhat sufficient for rehabilitating actionplanning or execution or restoration of unaffected physical actions orrelated cognitive processes. The present invention provides videogame-like, opportunities so that said user is able to transition frommere visualization to external feedback generation, i.e. to instantiateabstract mental representations of physical actions into actual visualdisplays of simulated physical actions, synonymously, “viewableembodiments of cortical simulations of physical actions.”

Existing theories hold that repeated stimulation of neurologicalreceptors may form “cell assemblies” and that there are beneficialmathematical relationships between outcomes of repeated firing ofinterconnected neurological cells and learned behavior. Using thepresent invention at least includes and provides for repeated,self-induced neurological stimulation and self-teaching, includinginteractive instantiation of kinetic imagery.

Using the present invention, the user may attempt to create simulatedphysical actions and may succeed in doing so. Consequently, the user'splanning processes for anticipated and intended physical actions andrelated cognitive processes are activated. This activation may befollowed by controlling and/or directing desired, purposeful, simulatedactions. Basically, the user anticipates or intends to originate orotherwise cause simulated physical actions and knows the meaning of suchactions. Using the methods and/or apparatuses of the present invention,which include utilizing or creating instantiated kinetic imageryfeedback, may help to illustrate and reinforce what the user planned todo and actually did. Repetition makes it possible to do that better.

SUMMARY

The following presents a simplified summary of one or more aspects ofthe present disclosure in order to provide a basic understanding of suchaspects. This summary is not an extensive overview of all contemplatedaspects, and is intended neither to identify key or critical elements ofall aspects nor to delineate the scope of any or all aspects. Its solepurpose is to present some concepts of one or more aspects in asimplified form as a prelude to the more detailed description that ispresented later.

The one or more users of the present invention are able to transitionfrom conscious imagery/visualization, in effect abstract mentalprocesses, to real visuomotor feedback. Accordingly, for said affectedconditions, injuries, disorders or experiences, or for any user who ischallenged, the present invention enables instantiation of kineticimagery, i.e. “viewable embodiments of cortical simulations of physicalactions” resulting in feedback that is next-best to actual physicalaction feedback for self-teaching, self-re-learning, self-re-exercisingphysical actions or skills or related cognitive processes orself-therapy-rehabilitation.

Aspects of the present invention relate to methods and apparatuses forinstantiating kinetic imagery. More particularly, the invention includesinstantiating kinetic imagery by a user controlling virtual body partsalone or in conjunction with virtual objects. In an aspect, a user mayengage in one or more self-teaching virtual training games, i.e.Pre-action Exercise Games (“PEGs”). PEGs provide users with stimulatingsubstitutes for actual physical action feedback. Said feedback fostersstimulation aspects of any user's brain previously compromised due toany of the conditions or disorders listed in this disclosure or otherconditions that may be within the scope of this disclosure. PEGs providesimulated physical action feedback from user controlled/directed virtualbody parts corresponding or non-corresponding to the user's body part(s)that may have suffered reduced or lost functionality. Said user,controlling virtual world actions, is engaged in virtual training forreal-world actions. In an additional aspect, PEGs provide a user with aneuronal workout that stimulates without limitation neuronalrecruitment, synaptogenesis or brain plasticity, functions or processes.

PEGs provide a link between kinetic visualization/imagery and useroriginated-controlled/directed simulated physical actions. Visualizationand imagery of physical action is an integral step in motor planning,physical performance or reacquisition of purposeful physical actionsthat have been compromised. The methods and apparatuses described hereinimplement kinetic imagery by providing each user with means to ‘act out’or otherwise control virtual body parts so that the simulated actions ofbody parts represent instantiated, real visual displays of a user'sabstract processes of visualization/imagery.

The present disclosure further relates to constructing, configuring,and/or controlling user controllable images, such as those used inpre-action training. According to aspects of the present disclosure,presented is a method of constructing a user-controllable image, whichincludes obtaining anatomical and physiological data associated with amodel of the body, storing said data in a database, and creating theuser-controllable image based on said body model data, wherein theuser-controllable image may be configurable to a user, wherein at leasta moveable portion of the user-controllable image is constructed to movebased on input controls from a user, and wherein the user-controllableimage is constructed so as to enable pre-action self-training by a user.In an additional aspect, demonstrative actions of the user-controllableimage or any image(s) can be generated by using motion capture or othertechnologies. In an additional aspect, motion capture or othertechnologies can likewise be used to construct and/or configure a usercontrollable image.

In an additional aspect, presented herein is a method of configuring auser-controllable image to a user, which includes obtaining at least onedefault parameter associated with the user-controllable image, obtainingat least one user parameter associated with a user body, comparing theat least one default parameter and the at least one user parameter,constructing a user-configured, user-controllable image by adjusting oneor more of the at least one default parameter where the at least oneuser parameter differs from the at least one default parameter, whereinthe user-configured, user-controllable image is configured so as toenable pre-action self-training by a user, and providing theuser-configured, user-controllable image to the user for pre-actiontraining. In an additional aspect, motion capture or other technologiescan likewise be used to configure a user-controllable image (“UCI”).

The present disclosure further provides an example method of controllinga user-controllable image, which includes providing a virtual body partto a user, wherein the user-controllable image comprises the virtualbody part, receiving a selection input or multiple selection inputs fromthe user, wherein said selection input(s) is associated with at least aportion of one or more virtual body parts, receiving an action inputfrom the user, and displaying an action of the at least a portion of thevirtual body part based on the action input, wherein the displayedaction is physically non-corresponding to the action input and whereinthe selection input(s) and action input(s) are at least a part ofpre-action self-training by a user. In addition, the present disclosurecontemplates without limitation apparatuses, computers, computerreadable media, hand-held devices, computer program products, internetaccessibility, multi-user use and means for performing these saidexample methods.

The present disclosure further relates to methods and apparatuses thatprovide for user pre-action control of non-virtual prostheses,exoskeleton body parts, robots or other motile or audiovisual devices,synonymously, “at least one non-virtual object.” This disclosureprovides an example method for controlling a UCI representing said atleast one non-virtual object. It includes providing a virtualrepresentation of a non-virtual object to a user, wherein saidrepresentation of a non-virtual object receives a selection input(s)from the user, wherein the selection input is associated with at least aportion of the non-virtual object, wherein receiving an action(s) inputfrom the user, and displaying, approximately simultaneously, saidvirtual action and a physical action of the at least a portion of thenon-virtual object and based on the action input, wherein the saidvirtual and physical actions are physically non-corresponding to theaction input and wherein the selection input and action input are atleast a part of pre-action training a user to use a non-virtual object.

Further aspects of the present invention relate to using PEGs formedical diagnostic purposes or measuring brain processes and biologicalsubstances, or biomarkers, to improve PEGs. In such further aspects ahealth-affected user, using PEGs, simultaneously has brain processes andbiological substances assessed or measured, then compared to a baselineof control non-health-affected users who have used or are using PEGs.

Further aspects of the present invention relate to healthcare orresearch professionals learning or researching “what-ifs” relating toany of the conditions to which this invention is applicable.

The methods and apparatuses of the present disclosure may benon-invasive, solo video game-like, heuristic, economical and useable onany computer or other digital device, practically anywhere and at anytime. The present invention has the potential to leverage users'rehabilitation or therapists' productivity to high levels. It iswell-suited to hands-on or telemedicine healthcare services.

To the accomplishment of the foregoing and related ends, the one or moreaspects comprise the features hereinafter fully described andparticularly pointed out in the claims. The detailed description of theinvention and the annexed drawings set forth in detail certainillustrative features of the one or more aspects. These features areindicative, however, of but a few of the various ways in which theprinciples of various aspects may be employed, and this description isintended to include all such aspects and their equivalents.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosed aspects will hereinafter be described in conjunction withthe appended drawings, provided to illustrate and not to limit thedisclosed aspects, wherein like designations denote like elements, andin which:

FIG. 1 is a system-level component diagram illustrating a system forpre-action training according to aspects of the present disclosure;

FIG. 2 is a component block diagram of aspects of a computer device forpre-action training according to aspects of the present disclosure;

FIG. 3 is a component block diagram of aspects of a UCI constructingdevice according to aspects of the present disclosure;

FIG. 4 is a component block diagram of aspects of a generic computerdevice according to aspects of the present disclosure;

FIG. 5 is a flow diagram illustrating aspects of an example method ofconstructing a UCI according to the present disclosure;

FIG. 6 is a flow diagram illustrating aspects of an example method ofconfiguring a UCI to a user according to the present disclosure;

FIG. 7 is a flow diagram illustrating aspects of an example method ofproviding pre-action training activities to a user according to thepresent disclosure;

FIG. 8 is a flow diagram illustrating aspects of an example method ofinstantiating a virtual movement and reinitiating neurologicalfunctionality according to the present disclosure;

FIG. 9 is a component diagram illustrating an example grouping ofelectrical components for creating a UCI according to the presentdisclosure;

FIG. 10 is a component diagram illustrating an example grouping ofelectrical components for configuring a UCI to a user according to thepresent disclosure;

FIG. 11 is a component diagram illustrating an example grouping ofelectrical components for providing pre-action training activities to auser according to the present disclosure;

FIG. 12 is a component diagram illustrating an example grouping ofelectrical components for instantiating kinetic imagery, i.e.embodiments of cortical simulation and reinitiating neurologicalfunctionality according to the present disclosure;

FIG. 13 is a representative drawing a non-virtual robot, prosthesis, orexoskeleton body part according to the present disclosure;

FIG. 14 is a representative wiring diagram of a non-virtual robotaccording to the present disclosure;

FIG. 15 is a representative wiring diagram of a non-virtual robotaccording to the present disclosure;

FIG. 16 is a block diagram illustrating a machine in the example form ofa computer system according to an example aspect of the presentdisclosure.

DETAILED DESCRIPTION

Purposeful and reflexive physical actions of body parts are proximallyderived from neuronal signaling (spinal cord outputs) to muscles.However, pre-action planning for purposeful actions is derived fromneuronal signaling (outputs) of brain structures or processes initiatingthe neural signaling of the spinal cord. Brain communications areessential to initiating purposeful new physical actions or to regainingability to perform said physical actions or related cognitive processesor to correct physical, neurological or psychological actions associatedwith disorders or conditions.

The damaged brain, no less than other damaged body parts, requirestherapy or rehabilitation. PEGs were and continue to be designed andused to stimulate pre-action planning processes for brain therapy orrehabilitation. No known technologies, other than those disclosed inthis disclosure are directed to pre-action planning, training, orexercises in virtual environments. None are known to enable users toinstantiate kinetic imageries of physical actions in any virtualenvironment i.e. to originate or create viewable embodiments of corticalsimulations of physical actions.

Acquired brain injury (“ABI”), including stroke, chronic traumaticencephalopathy, and traumatic brain injury (“TBI”), survivors or withoutlimitation individuals affected by any condition, disorder, orexperience noted in this disclosure, may sustain impaired or eradicateduse of one or more body parts. The result is formation of mild to severebarriers to physically controlling one's actions. The barriers existdespite, in many instances, body parts being totally or somewhatuninjured. For ABI survivors it is fair to say that except for the braininjury (and consequential atrophy) chronic physical action deficitswould not require rehabilitation. To address said deficits ABI survivorsundergo long-term and costly therapeutic and rehabilitative procedures.These are major healthcare services or cost problems. Epidemiologically,and by way of example, the combined, annual incidence of ABI, stroke andtraumatic brain injury (“TBI”) alone, in the United States leaves 2.5million survivors annually. A broader category, neurotrauma (penetratingand non-penetrating), including primary brain tumor, focal dystonias,limb apraxia/ataxia, cerebral palsy and amputations, affects more than12 million U.S. civilians and approximately 200,000-400,000 combatveterans. Assuming that the incidence of ABI/TBI alone is generallyuniform worldwide, by extrapolation the total number of ABI/TBIsurvivors worldwide would exceed 50 million individuals. The totalnumber of neurotrauma survivors worldwide would therefore exceed 275million individuals, which represents a number approximating the entireU.S. population.

Conventional rehabilitation/therapies for treating ABIs are primarilyphysical in nature involving assisted and independent efforts to restoresurvivors to being able to make unaffected physical actions. Physicaland occupational therapy actions are characterized in that the movementsof survivors' body parts correspond to intended unaffected movements.For example, when a user recovering from a stroke or TBI undergoesrehabilitation to regain proper axial movement of the user's arm at theshoulder, the user with or without assistance repeatedly attempts tomove (or have moved with professional or mechanical assistance) her/hisarm in the axial direction. Those movements are to promote recoveryaccording to conventional therapy or rehabilitation emphasizingcorresponding movements. That recovery process is predominantlyoutside-in. In contrast, the processes of the present invention areinside-out. Methods and apparatuses for pre-action training target brainstructures or processes, i.e. a principal pathological site for ABI/TBIsurvivors or other affected individuals.

Making corresponding physical training movements are variably effective,but difficult or impossible for those recovering from ABI/TBI or otherconditions or disorders noted above. From the survivors' perspective,the challenge and question are how to practice physical actions or trainto move without being able to move. ABI/TBI survivors are left withdisconnections between, on one hand, intact, and in many cases,initially uninjured body parts and on the other hand, dysfunctionalbrain processes required for planning the movements of such body parts.In some cases, patients' and survivors' difficulties are magnified dueto the individual's non-awareness of the existence of an unusable bodypart. One challenge for ABI/TBI survivors is to regain the use of bodyparts. That challenge is addressed by using the present invention tocontrol virtual body parts so as to make simulated actions before,during, after or adjunctive to utilizing physical or assistiverehabilitation or therapeutic methods that use corresponding physicalactions by such body parts. Thus to regain full and expeditious controlof using ABI/TBI-affected body parts the present methods and apparatusesare needed for providing pre-action training.

Conventionally for ABI, at least one of three therapies is used. Theyare, motor imagery; mirror therapy; and action-observation therapy.Motor imagery involves imagining motor controls and attempting tophysically exercise the resulting imagery. Mirror therapy has been usedfor amputees experiencing phantom limb pain. It involves using an intactbody part to make physical actions reflected in a physical mirror. Themirrored actions appear to be made by the contralateral (amputated) bodypart. The patient's observation of said actions has been shown todecrease or terminate phantom limb pain Action-observation therapy istheoretically mirror neuron based and involves viewing physical actionsfollowed by the patient's efforts to match i.e. imitate the observedactions. None of the foregoing therapies are video game-like in terms ofinteractivity, immersion, scope, versatility, heuristic teachingmethodology, economy, or entertainment. None enable patients toinstantiate kinetic imagery as does the present invention. The presentinvention, unlike current therapies or rehabilitation techniques enablesindividuals, in a video game-like virtual environment, to independentlymake inputs that interactively control virtual body parts. By personallycausing simulated physical actions to be displayed, said individualsproduce real visuomotor (visuoaction) feedback from said simulatedactions and induce new or augmented brain processes.

Humans excel at creating mental imagery. Imagery and simulation occurwhile conscious or during dreams. Conscious, imagined actions precedeand are fundamental to making purposeful physical actions. Makingrepeated physical actions, accompanied by feedback acquired from suchactions, results in improved action skills. For unaffected individuals,the process of creating productive feedback evolves from mentalabstractions to making actual physical actions in the real world andreceiving feedback via sensory-action return signals. That process isvariably unavailable or impossible for many individuals affected by theaforementioned conditions. However, for said affected individuals thepresent invention may be used to create productive action feedbackdirected to improving action planning or regaining physical actions fordaily living.

Aspects of the present invention relate to methods and apparatuses forpre-action training, also disclosed as pre-action training for ABI/TBIsurvivors. The term ABI/TBI survivors in this disclosure includeswithout limitation other conditions and disorders disclosed in thisdisclosure and others to which pre-action training may be useful. Moreparticularly, the invention is for pre-action training by ABI/TBIsurvivors using virtual body parts. In an aspect, a user, who may be anABI/TBI survivor, may engage in one or more Pre-Action Exercise Games(“PEGs”). PEGs provide ABI/TBI survivors with brain stimulatingsubstitutes for actual physical-action feedback. Said PEGs feedbackfosters the user's restoration of pre-action brain processing, such asthose parts of the brain previously compromised due to the ABI/TBI. PEGsprovide simulated physical-action feedback from user-originated physicalsimulations via controlled/directed, virtual body parts corresponding toat least the user's body parts that suffered reduced or lostfunctionality as the result of ABI or TBI. Such survivorcontrolled/directed, virtual body parts are caused by the user tosimulate physical actions thereby executing virtual-world actions aspre-action training for real world actions. In an additional aspect,PEGs provide the ABI/TBI survivor with a pre-action training workoutthat stimulates without limitation neuronal recruitment, inter-neuroncommunication synaptogenesis and brain plasticity.

PEGs provide a link between kinetic imagery/visualization anduser-originated simulated physical actions. Imagery/visualization ofphysical actions is integral to action planning, physical performance,and reacquisition of physical actions or skills. The methods andapparatuses described herein support kinetic visualization and imageryby providing each user with means to ‘act out’ or otherwise controlvirtual body parts so that the body parts represent real visualinstantiations of a user's abstract processes of imagery/visualization.

PEGs are without limitation exercises used in pre-actioncontrol/direction of virtual body parts to simulate physical actionintentions and at least to receive feedback for neuro-rehabilitation ofaction-planning processes.

According to aspects of the present disclosure, interaction with virtualbody parts, links any user's cognition, visualization, or imagery tovirtual action feedback. Furthermore, the methods and apparatusesdescribed herein can engage ABI/TBI survivors to self-teach actionplanning for purposeful physical actions.

According to aspects of the present disclosure, an ABI/TBI survivor maytarget and help overcome her/his action deficits by making inputs to asystem that displays a user-controllable virtual body part, therebydirecting and causing simulated actions of a moveable region of thevirtual body part based on the inputs, viewing feedback from suchsimulated actions and building new and/or re-building impairedneurological or brain processes

According to the present disclosure, any user may control and directvirtual body part(s) to display simulated, human physical actions withvirtual full range of motion. The user may control a virtual body partto speed up, slow down, stop or make any combination of said actions orgradations of same. System displays of virtual body part actions may beidiosyncratic representations of each survivor's input controls anddirection. In effect, the user's virtual body part control processstimulates cognitive processes and pre-action-trains for real actionprocesses.

Furthermore, the methods and apparatuses presented herein differ frommodern gaming systems like Wii™ and Kinect™ that are being used forphysical and occupational rehabilitation. Said systems require theirusers to make actual physical actions that are then displayed in virtualenvironments. Therefore, by design, Wii™ and Kinect™ users make actualphysical actions that correspond to displayed actions. Conversely, themethods and apparatuses presented herein eliminate the requirement ofuser performance of corresponding physical actions to what are thendisplayed as simulated physical actions. For example a user of thepresent invention can make small or limited non-corresponding eye and/orhead gestures carried by webcam signals, and wirelessly transmit brainsignals, to control the simulated actions of virtual body parts. In butone example, any user's input signals by eye controls (alone) can directa virtual shoulder to move an arm 90 degrees away from the body.Accordingly, a user's input signaling processes associated with thepresent invention are non-corresponding, that is to say a user'sphysical method of input, e.g. eye, mouse or wireless brain signal, doesnot correspond to the simulated actions of the virtual body parts of thepresent disclosure.

The inputs (controls and directions) described herein are dissociatedfrom displayed virtual-image actions and allow ABI/TBI survivors tocause simulated physical actions (action processes) before and withoutperforming real physical training action processes. Each user's inputsaccording to the present disclosure are not physical-training actionmovements of the desired drill or skill. Rather, the present methods andapparatuses target without limitation neuronal systems, brainstructures, gray and white matter circuitry, neurogenesis,synaptogenesis, myelination, brain plasticity, and cognitive processes,not any particular physical-action inputs or outputs.

Physical training participation, due to its repetitive aspects, can betedious and hindered by boredom. Participation in physical training isalso fraught with new injury or aggravating old injury. PEGs provideentertaining, rewarding, and immersive features, including game sequenceactions that result from a user's successful control, direction, andmanipulation of virtual body parts and objects or non-virtual robots,prostheses or exoskeleton body parts.

For example, in terms of non-limiting and non-exclusive variations ofresearch and investigation as well as practical application, monitoringbrain activity can enhance PEGs' pre-action training value. ABI/TBIsurvivors' brain activities or processes can be measured through anybrain imaging technology or by analyzing blood and/or other body fluids,or biomarkers, or other substances for particular bio-chemicals,markers, and/or compounds related to without limitation overall braincortical, or cognitive activity. ABI/TBI survivors' baseline brainactivities or processes could be determined before, during and afterPEGs training to measure changes accompanying PEGs training.Additionally, ABI/TBI survivors' brain activities or processes can becompared to non-ABI/TBI affected individuals undergoing or who underwentPEGs training activities to determine whether PEGs training isstimulating the same or similar affected parts of the ABI/TBI survivors'brains as are stimulated in the non-ABI/TBI affected individuals'brains. PEGs can be adjusted accordingly to enhance the brain activityor processes in the identified brain structures, processes or circuitryof the ABI/TBI survivors to match brain activities (including substancequantities, levels, and the like) of non-affected individuals' brainstructures, processes or circuitry accompanying PEGs training. Othernon-limiting and non-exclusive variations on the process are discussedbelow.

PEGs can also be used as a non-invasive diagnostic tool. Some ABI/TBIsurvivors suffer mild brain injury, however current diagnostics arelimited, comprising mostly subjective tests and some technical means.Additionally, while moderate to severe ABI/TBI is detectable throughchanges in brain morphology by CT-scans, MRI or other imagingtechnologies, mild ABI/TBI is difficult to detect or diagnose. Anysurvivor, who does not show severe or moderate TBI, could also beintroduced to playing PEGs to monitor for mild ABI/TBI. Potentiallymildly affected patients would play PEGs, and her/his brain activitieswould be compared to unaffected individuals' baseline brain activitiesto determine the comparative state or extent of mild injury or thepossibility of unlikely or no detectable injury. PEGs may be used forassessing other levels of ABI/TBI, either solo or in conjunction withother methods or devices.

Various aspects are now described with reference to the drawings. In thefollowing description, for purposes of explanation, numerous specificdetails are set forth in order to provide a thorough understanding ofone or more aspects. It may be evident however, that such aspect(s) maybe practiced without these specific details. Turning to FIG. 1, a system100 is presented for presentation and manipulation of a virtual bodypart as means for pre-action training a user. In an aspect, system 100may include a computer device 102, an input device 104, a display device106, and a user measurement device 108. Additionally, system 100 mayoptionally include an external body part device 128 and/or a feedbackdevice 130. According to an aspect, computer device 102 may beconfigured to receive and process one or more user inputs 110 from inputdevice 104, one or more user characteristics 112 from user measurementdevice 108, and may also be configured to generate and transmit one ormore display control messages 114 to display device 106. In addition,computer device 102 may be configured to execute manipulation of adisplayed virtual body part based on at least the inputs 104 of user120.

Furthermore, computer device 102 may include a processing engine 116,which may be configured to receive, process, and transmit signalsassociated with display, control, and/or behavior of a virtual bodypart. Additionally, computer device 102 may include a memory 118, whichmay be configured to store user characteristics (such as neurological orchemical characteristic values observed and/or measured from a user 120)and/or instructions for executing one or more PEGs.

In an aspect, input device 104 may be configured to receive one or morephysical or non-physical inputs 122 from a user 120 and process andforward the processed physical inputs to computer device 102 as inputs110. In an aspect, input device 104 may be any means of receiving directphysical input from a user 120, such as, but not limited to a keyboard,mouse, touch pad, smart phone, laptop, smart phone, computer or genericcomputing device, an input device that senses input without interventionof the user, etc. Alternatively or additionally, input device 104 may bea device configured to generate input 110 by recognizing and processingone or more user actions at user action recognizing component 124. Forexample, in an aspect, user action recognizing component 124 may beconfigured to recognize user inputs via, by non-limiting example, eyeaction, nominal physical action of hands or other body parts, blinking,nodding, and/or by detecting and monitoring neurological signalsgenerated by the user's body. For example, user action recognizingcomponent 124 may include a component capable of reading instructionssignaled in the brain, spinal cord, or any other neurological circuit ortissue of the user 120.

Furthermore, display device 106 may be configured to display a virtualbody part and actions of the virtual body part. In an aspect, displaydevice 106 may display the virtual body part visually on a screen ordisplay, such as, but not limited to, a computer monitor, projector,television, or the like). Alternatively or additionally, external bodypart device 128 may receive one or more external body part controlsignals 132, which may cause the external body part device 128 to move,for example, by mechanical means. In an aspect, external body partdevice 128 may be, but is not limited to being, a robotic arm, shoulder,or the like. In some examples, the external body part device 128 maystand alone and be placed in a location viewable by the user 120.Additionally, the external body part device may be attached to the user120, which may allow the user to witness more “true to life” actionsassociated with his or her physical inputs 122.

In yet another aspect, system 100 may include a feedback device 130configured to provide feedback 136 to the user 120. In an aspect,feedback device 130 may receive one or more feedback control messages134 related to the feedback device from computer device 102, which maygovern the action and behavior of the feedback device 130. In an aspect,feedback 136 may include, but is not limited to, force feedback,pneumatic feedback, auditory or visual feedback, non-force feedback, orany other form of feedback that may indicate an output of computerdevice 102 related to pre-action training. For non-limiting example,feedback device 130 may be a mechanical device that a user may attach tohis or her hand or arm that may provide force feedback to the user'shand or arm in order to bend the user's wrist. In such an example, thisbending may occur where the user selects a virtual wrist on displaydevice 106 and moves the virtual wrist up and down (or in any direction)by moving input device 104. Based on this input, processing engine 116may generate and transmit a feedback control message 136 to the feedbackdevice 130—here, the mechanical device—which may provide a force to theuser's wrist to move it substantially in unison with the action of thevirtual image, which may be displayed on display device 106concurrently.

In an additional aspect, system 100 may include a user measurementdevice 108, which may be configured to measure one or more usercharacteristic values before, during, and/or after engaging inpre-action training activities. In some examples, user characteristicvalues may include without limitation neurological or chemical data,pulse, blood pressure, or any other measureable characteristic orphysical parameter of an animal, which may include a human being. In anaspect, user measurement device may utilize imaging technology tomeasure these user characteristics, and such imaging technologies mayinclude, without limitation, Magnetic Resonance Imaging (MRI),Functional Magnetic Resonance Imaging (fMRI), Computed Tomography (CT),Positron Emission Tomography (PET), Electroencephalography (EEG),Magnetoencephalography (MEG), Near-infrared spectroscopy (NIRS), andHigh Density Fiber Tracking (HDFT).

In a further aspect, user measurement device 108 may send the measureduser characteristic data 112 to computer device 102 upon measurement.There, the user characteristic data may be (a) stored in memory 118 forlater use or (b) fed to processing engine 116 as feedback data thatprocessing engine 116 may utilize to alter an ongoing pre-actiontraining activity, such as an ongoing PEG, or may be used to diagnose amedical condition. Alternatively, where the user characteristic data isstored in memory, such data may be used to tailor future pre-actiontraining activities to the user's individual characteristics or currentskill level or to track the progress of a user over time, or to improvePEGs.

Turning to FIG. 2, an illustration of components comprising computerdevice 102 (FIG. 1) is provided. In operation, computer device 102 maypresent an initial or default virtual body part to a user, for example,when the user, trainer, coach, therapist, or any other type of userinitially boots up computer device 102, selects a PEG 226 for pre-actiontraining activities, or the like. To display this default virtual bodypart, virtual body part manager 204 may query memory 118 for defaultparameters 224 of a set of physical characteristic values 220 storedthereon and may process and display the default virtual body part bysending, for example, one or more display control signals to a display.In addition, once the user begins a pre-action training session,computer device 102 may receive inputs from the user, such as, but notlimited to, selection inputs and action inputs. Based on these one ormore inputs and pre-stored and executable PEGs 226 located in memory118, the computer device may present a selectable, movable, andotherwise interactive virtual body part with which a user may engage topartake in pre-action training activities.

As previously outlined, computer device 102 may include processingengine 116 and memory 118—the operation and composition of which will beexplained in reference to FIG. 2. First, processing engine 116 may beconfigured to process one or more input signals and transmit theprocessed signals to a display device for presentation of auser-controllable image, such as a virtual body part, to a user. Forpurposes of the present description, a user-controllable image (UCI) maybe all or part of a virtual body part or object controllable by userinput to simulate physical actions, wherein these physical actions arenon-corresponding to the user's physical actions in generating the userinput. Examples of UCIs described herein may comprise a virtual bodypart or virtual body parts, but the scope of such examples should not belimited thereto.

In an aspect, processing engine 116 may include a PEG executioncomponent 202, which may process user inputs to generate display controlmessages according to instructions related to one or more PEGs. In anon-limiting example, a user may select a particular PEG to play and asa result, PEG execution component 202 may load the PEG instructions fromPEGs 226 stored in memory 118. After loading the PEG, the PEG executioncomponent 202 may generate one or more display control messages fortransmission to a display device based on the PEG and any input messagesreceived from an input device. Furthermore, in an aspect, PEG executioncomponent 202 may be configured to alter one or more PEGs based onfeedback from a user measurement device. In a non-limiting example, PEGexecution component 202 may receive an indication that a user'sneurological system is stronger than in the past and may make playing aparticular PEG more difficult to maximize further neurologicalimprovement.

In an additional aspect, processing engine 116 may include a virtualbody part manager 204, which may be configured to virtually constructand manage action of a virtual body part that computer device 102 maygenerate for display on a display device. Furthermore, for purposes ofthe present description, the term “display device” may correspond todisplay device 106, external body part device 128, feedback device 130,or any other device or means capable of producing output correspondingto an action, and/or status of a virtual body part, including outputresulting from user input during pre-action training activities.

In an aspect, virtual body part manager 204 may include a selectioninput managing component 206, which may be configured to receive one ormore selection inputs from a user or an input device manipulated by auser, wherein the selection inputs may correspond to a user selecting avirtual body part or a portion thereof. Furthermore, based on aselection input, selection input manager 206 may map a select locationassociated with a selection input to a virtual body part or a portionthereof, which may correspond to a virtual body part selected forsubsequent or concurrent action by the user.

Furthermore, virtual body part manager 204 may include an action inputmanager 208, which may be configured to receive one or more actioninputs from a user and generate one or more display control signals thatcause displayed action of the virtual body part. In an aspect, thisdisplayed action may correspond to the virtual body part or portionthereof selected by the user and mapped by selection input manager 106.Additionally, action input component 206 may generate and display thedisplayed action based on the user “dragging” “pointing” “tapping”“touching” or otherwise correctly manipulating at least a portion of themoveable body part.

Furthermore, action input component 206 may base its virtual body partaction generation and/or other processing actions on a particular PEG,which may have been pre-selected by a user and loaded for execution byprocessing engine 116. In an aspect, an action input may be input by auser and received by computer device 102 as a result of the userpartaking in such a PEG, other pre-action training activity, or anyother pre-action training activity. Additionally, in an aspect of thepresent disclosure, a user input action may be physicallynon-corresponding to the desired or eventual action of the displayedvirtual body part with which the user is interacting. For purposes ofthe present disclosure, a non-corresponding action may be a user actionthat differs relatively significantly from a displayed action. Fornon-limiting example, suppose a user engaged in a pre-action trainingactivity wishes to move a virtual forearm directly upward using a mouseas an input device. To do so, according to aspects of the disclosure,the user may first navigate a cursor and click a mouse button to selectthe virtual forearm on a display device, thereby inputting a selectioninput. Next, the user may keep the cursor on the virtual forearm and mayhold the mouse button down to signal a beginning of an action input.Thereafter, the user may drag the mouse two inches along a mouse pad,with the mouse button held down, and may observe the virtual forearmrise upward, for example, from a virtual hip area to a virtual headarea. To carry out this action, the user's forearm may have movedapproximately two inches in a direction parallel to the mouse pad, butresulted in a virtual action of the virtual forearm that was upward indirection and appeared greater than two inches in magnitude. Therefore,this example user input action is non-corresponding to the action of thevirtual body part.

Additionally, virtual body part manager 204 may include a demonstrativeaction manager 210, which may be configured to provide display controlmessages to a display device to effectuate a demonstrative action of thevirtual body part. For example, demonstrative action manager 210 maystore and/or execute a retrieved demonstrative action to be displayed tothe user as a “ghost” action. In an aspect, the user may view thedemonstrative action and may then attempt to manipulate the virtual bodypart to mimic the action of the demonstrative action or ghost action.

Furthermore, virtual body part manager 204 may include a user-configuredUCI manager 212, which may tailor or otherwise configure a displayedvirtual body part to a user's body and/or alter the behavior of thedisplayed virtual body part based on one or more user characteristicvalues 222. In an aspect, such characteristics may include anatomicaland physiological data characteristic values associated with the user,such as without limitation height, weight, arm length, muscle mass,TBI-affected body parts, handedness, age, gender, eye/hair/skin color,and the like. In additional or alternative aspects, the usercharacteristics may include historical PEG performance data associatedwith the user, current neurological or chemical measurementcharacteristics or parameter values, or the like.

In an aspect, user-configured UCI manager 212 may obtain these usercharacteristic values 222 from memory 118. Alternatively,user-configured UCI manager 212 may obtain these user characteristicvalues from a source external to memory 118, such as, but not limitedto, a user measurement device configured to measure neurological and/orchemical characteristics of the user during pre-action trainingactivities, by querying a user or the user's trainer, doctor, coach,therapist or rehabilitation specialist for such characteristic valuesand receiving a characteristic value input in response, or otherwisereceiving user-specific performance, anatomical, physiological, or othercharacteristic values.

In addition, user-configured UCI manager 212 may be configured tocompare the user characteristic values, or user parameters, to one ormore default parameters 224 stored in memory 118. In an aspect, defaultparameters 224 may comprise the parameters of a default virtual bodypart of the present disclosure, and may include without limitationanatomical and physiological data (e.g. handedness, strength, bonelength, limitations on range of motion, skin characteristics, and thelike). Such characteristics may conform the behavior and attributes ofthe default virtual body part displayed to a user before tailoring,configuring, or otherwise customizing the virtual body part to the user.In order to perform such customization, the user-configured UCI manager212 may compare the obtained user characteristic values (e.g. usercharacteristic values 222) to default parameters 224. In an aspect,where the comparing determines that a user characteristic value differsfrom the default parameter value for a characteristic, theuser-configured UCI manager may set the compared parameter of thevirtual body part to be displayed to the user's characteristic value.Alternatively, where an obtained user characteristic value does notdiffer from the default parameter, user-configured UCI manager 212 mayleave the compared parameter unchanged.

In an additional aspect, processing engine 116 may be configured togenerate and/or transmit one or more display control signals to thedisplay device to effectuate action of the virtual body part.Furthermore, processing engine 116 may be additionally configured tocalculate and/or report an action degree or action magnitude associatedwith an action of the virtual body part. In an aspect, processing engine116 may display the calculated action degree or action magnitude bygenerating one or more display control messages, which may be generatedand transmitted in substantially real time, for transmission to adisplay device for visual indication of the action degree to the user.

Furthermore, computer device 102 may include a memory 118, which may beconfigured to store information for utilization by other components in asystem, such as, but not limited to, processing engine 116. Suchinformation may include physical characteristic values 220, which mayinclude user characteristic values 222 associated with one or more usersand/or default parameters 224 associated with a baseline or default UCI,such as a virtual body part. Furthermore, memory 118 may storeneurological, chemical, or any other data related to a user's body (e.g.without limitation neurological signaling data or maps, neuron activitydata, etc.) generated and/or observed by a user measurement devicebefore, during, and/or after a user engaging in pre-action training.Such data may also be fed back to processing engine 116, which may altera current or future PEG or pre-action training activity based on thefeedback.

In an additional aspect, such user data may be used to diagnose one ormore medical conditions. For example, computer device may output theuser data to a physician or other professional, who may analyze the dataand diagnose the medical condition. In an alternative or additional andnon-limiting example, computer device 102 may contain instructionsexecutable by processing engine 116 to automatically diagnose a medicalcondition based on the user data stored on memory 118.

In addition, memory 118 may include executable instructions (e.g.executed by processing engine 116), that when performed, allow the userto engage in one or more pre-action training activities. As used herein,pre-action training activities may include interactive electronic gamesor activities, such as, but not limited to, Pre-Action Exercise Games(PEGs) 226. The PEGs 226 may govern the behavior of a virtual body partin response to one or more inputs by a user during pre-action trainingactivities.

Additionally, cognitive function is involved in all PEGs. According tosome example PEGs, virtual upper body parts are presented to a user tocontrol in order to simulate purposeful physical actions—for example,opening and closing a virtual hand. Some PEGs may be virtual task games,which may couple player control of virtual body parts and objects toaccomplish tasks and/or solve problems—for example, dropping a spooninto a cup.

Furthermore, upper extremity exercises of some non-limiting example PEGsmay include player control of any part or all of an affected hand, loweror upper arm (right or left), executing flexion/extension,supination/pronation, abduction/adduction, or any other extremity orbody part action in any direction. According to the PEGs contemplatedherein, users can manage displays of some of, the majority of, or all ofa virtual upper extremity from substantially any angle. Additionally,the virtual body part may comprise fingers, which may be manipulatedindividually or in combination. The virtual body part may comprise awrist, which may be flexed/extended, abducted/adducted, orsupinated/pronated. Furthermore, according to some non-limiting examplePEGs, the virtual body part may comprise an arm, wherein the lower andupper arm may be manipulated independently or in combined action of anyand all joints of the arm, wrist and hand.

In some non-limiting example PEGs where the virtual body part is avirtual hand, example games for pre-action training may include:

-   -   pincer action to grasp a key    -   two finger action to grasp a ball and drop it into a cup    -   multi-finger action to pick up a spoon and drop it into a cup    -   full hand grasp around a mug handle    -   tapping actions by index and middle fingers on a remote        controller    -   hand grasps of objects shaped as stars, circles or squares, then        placement in similarly shaped slots.

Regarding virtual arms in some non-limiting example PEGs where thevirtual body part includes a virtual arm and/or a virtual hand, examplegames for pre-action training may include:

-   -   opening a correct box, i.e. selecting and opening the correct        numbered and colored box (e.g. purple 24) in a circle of nine        boxes, after observations and computations as elementary as        choosing the (single) “lowest purple box bearing an even number”        (purple 24 is correct) to computations based on several numbered        boxes, e.g. “choose the highest blue even numbered box, subtract        the second of its numbers from the first, square it and find the        green box with that result” (if 92 blue is selected the        subtraction yields number 7, which when squared is 49, so green        box 49 is correct)    -   same as above, nine box game with voice instructions to the        player    -   similar open the box game in a more elementary vertical        presentation of five boxes    -   light bulb game requiring the player to unscrew a light bulb,        choose the correct lettered socket and screw the bulb into the        correct socket    -   playing card games, for example in a simple game the virtual arm        and hand are controlled to select a pair of twos, place that        pair, right side up on a surface, then the player must choose        the lowest numbered pair that wins over a pair of twos,        alternately the highest numbered pair that wins over twos, then        the lowest (or highest) pair of picture cards that wins over        twos and so forth, to more complex combinations of playing        cards/hands    -   puzzle games in which the cursor is used to move 6, 9 or 16        puzzle pieces to assemble a complete representation of any        display noted above. For example, a hand image, in any        orientation, position and configuration may be disassembled by        the puzzle game into 6, 9 or 16 puzzle pieces to be reassembled        by the player, or a more complex disassembly of the nine box arm        game may be “puzzled”    -   simple number game displaying 0-9 and processes (add, subtract,        multiply, divide and equals sign) and calling for the PEGs        player to use a virtual arm and hand to select numbers and        processes and to make any number of computations by arraying the        numbers and processes accurately    -   simple letter game displaying all letters of the alphabet and        calling for the PEGs player to use a virtual arm and hand to        select letters to make any number of words by arraying the        letters accurately.

Where the virtual body part is at least one virtual muscle, games forpre-action training may include selection of said at least one virtualmuscle to cause it to contract or relax at any rate of speed or to stop,for non-limiting example to end cramping or focal cervical dystonia orto regain movement impeded by hand dystonia.

Therefore by loading and/or executing the one or more stored PEGs 226 ofmemory 118, computer device 102 may present a user with a UCI, such as avirtual body part, with which the user may interact to participate inpre-action training activities.

Turning to FIG. 3, the figure illustrates an example UCI creating device300 that facilitates creation of UCIs, including one or more virtualbody parts. In an aspect, UCI creating device 300 may include ananatomical and physiological data obtaining component 302, which may beconfigured to obtain anatomical and physiological data associated withone or more animal species, including, but not limited to, human beings.Such anatomical and physiological data may be accurate or relativelyaccurate anatomical and physiological data to ensure that a relativelylife-like UCI may be created therefrom. In a non-limiting example,anatomical and physiological data obtaining component 302 may beconfigured to interface, communicate with, read, extract data from, orobtain data from an external device or component that contains suchanatomical and physiological data, such as, but not limited to a server,a device connected to a network (e.g the Internet), a wireless device,or a device connected to UCI creating device by hard wire communicationline. In an additional aspect, anatomical and physiological dataobtaining component 302 may be configured to prompt a user to manuallyinput anatomical and physiological data and receive such data from auser via an input device such as, but not limited to, a keyboard.

Additionally, UCI creating device 300 may include a memory 304, whichmay include one or more databases 306 for storing and organizing data.In an aspect, database 306 may store anatomical and physiological data308, which may have been obtained via anatomical and physiological dataobtaining component 302.

Furthermore, UCI creating device 300 may include a UCI creatingcomponent 310, which may be configured to receive one or more inputs,such as, but not limited to program instructions, from a user (e.g. UCIarchitect, programmer, graphic designer), wherein the inputs, whenexecuted, construct a UCI. In an aspect, the received inputs mayconstruct the UCI based on the stored anatomical and physiological data308. Furthermore, UCI creating component may include an executableprogram, such as an image design program, graphics creation suite,programming/compiling engine, or rendering suite, which UCI creatingcomponent 310 may execute to receive the one or more inputs from theuser. These one or more inputs may define the physical parameters of theUCI, such as, but not limited to the bone length, bone interaction andposition, tendon length and position, skin tone, and the like.Furthermore, the inputs may form computer-executable instructions thatdefine and/or otherwise control the behavior of the UCI or portions ofthe UCI when executed, displayed, and interacted with by a user, forexample, during pre-action training such as when playing a PEG. Inaddition, inputs may define the behavior of virtual body parts adjacentto the selected or moved body parts such that action of one virtual bodypart or portion thereof causes related action of the adjacent virtualbody part or a portion thereof.

Moreover, UCI creating device 300 may include a PEG creating component312, which may be configured to create one or more PEGs by receiving oneor more inputs, such as, but not limited to program instructions, from auser (e.g. PEG architect, programmer), wherein the inputs, whenexecuted, construct a PEG. The created PEG may be created for purposesof pre-action training and may be programmed to alter the behavior of aUCI, such as a virtual body part, based upon user inputs. Furthermore,the PEG may be programmed to customize or tailor a PEG based on uniquecharacteristic data associated with the user, such as, but not limitedto, height, weight, historical PEG performance, handedness, extremitylength, and the like.

Referring to FIG. 4, in one aspect, generic computer device 400 mayinclude a specially programmed or configured computer device, and mayrepresent or contain components that may be included in computer device102 FIGS. 1 and 2) or UCI creating device 300 (FIG. 3). Generic computerdevice 400 includes a processor 402 for carrying out processingprocesses associated with one or more of components and processesdescribed herein. Processor 402 can include a single or multiple set ofprocessors or multi-core processors. Moreover, processor 402 can beimplemented as an integrated processing system and/or a distributedprocessing system. Additionally, processor 402 may be configured toperform the processes described herein related to UCI behavior and/orpre-action training on the generic computer device 400.

Generic computer device 400 further includes a memory 404, such as forstoring data used herein and/or local versions of applications beingexecuted by processor 402. Memory 404 can include any type of memoryusable by a computer, such as random access memory (RAM), read onlymemory (ROM), tapes, magnetic discs, optical discs, volatile memory,non-volatile memory, and any combination thereof. Additionally, memory404 may be configured to store data and/or code or computer-readableinstructions for performing the processes described herein related tocreating, controlling, manipulating, and/or instantiating a UCI.

Further, generic computer device 400 includes a communications component406 that provides for establishing and maintaining communications withone or more entities utilizing one or more of hardware, software, andservices as described herein. Communications component 406 may carrycommunication signals between components on generic computer device 400,as well as exchanging communication signals between generic computerdevice 400 and external devices, such as devices located across a wiredor wireless communications network and/or devices serially or locallyconnected to generic computer device 400. For example, communicationscomponent 406 may include one or more buses, and may further includetransmit chain components and receive chain components associated with atransmitter and receiver, respectively, or a transceiver, operable forinterfacing with external devices.

Additionally, generic computer device 400 may further include a datastore 408, which can be any suitable combination of hardware and/orsoftware, that provides for mass storage of information, databases, andprograms employed in connection with aspects described herein. Forexample, data store 408 may be a data repository for applications anddata not currently being executed by processor 402, such as thoserelated to the aspect described herein. In addition, generic computerdevice 400 may contain an input/output component 410, which may beconfigured to interface with one or more external devices, such as aninput device (e.g. input device, user measurement device (FIG. 1))and/or an output device (e.g. a display, feedback device, or externalbody part device (FIG. 1)). Specifically, input/output component 410 maycontain circuitry and/or instructions that allow generic computer device400 to connect to and/or communicate with these external devices.

In reference to FIG. 5, provided is an example methodology 500 forcreating or otherwise constructing a user-controllable image, such as avirtual body part. In an aspect, at block 502, a user (e.g. a programengineer, user, or graphics engineer) or computer device may obtainanatomical and physiological data associated with a body. Once obtained,at block 504, the user or computer device may store the anatomical andphysiological data in a database. In addition, at block 506, the user orcomputer device may create the user-controllable image based on thestored anatomical and physiological data. Furthermore, the createduser-controllable image may be configurable to a user. Additionally,according to some example methods, at least a moveable portion of theuser-controllable image may be constructed to move based on input from auser, for example, so as to enable pre-action training the user.

Furthermore, FIG. 6 presents an example methodology 600 for configuring,tailoring, or otherwise customizing a UCI or related PEG to a particularuser. Such a method may be performed by a computer device, but may alsobe performed or controlled via a computer device by an individual, e.g.a pre-action training coach, therapist, or doctor, who may guide a userthrough a pre-action training regimen. In an aspect, at block 602, theindividual or computer device may obtain at least one default parameterassociated with the user-controllable image. In addition, at block 604,the individual or computer device may obtain at least one user parameterassociated with a user body. Furthermore, at block 606, the individualor computer device may compare the at least one default parameter andthe at least one user parameter. Moreover, the individual or computerdevice may construct a user-configured user-controllable image byadjusting one or more of the at least one default parameter. In anaspect, such an adjustment may be made where the at least one userparameter differs from the at least one default parameter. Additionally,the user-configured user-controllable image may be configured so as toenable pre-training a user, and as such, at block 610, the individual orcomputer device may provide the user-configured user-controllable imageto the user for pre-action training.

Turning to FIG. 7, an example methodology 700 is presented forpresenting a controllable virtual body part to a user. In an aspect, atblock 702, a computer device may provide a virtual body part to a user.Furthermore, at block 704, the computer device may receive a selectioninput from the user, wherein the selection input is associated with atleast a portion of the virtual body part. Additionally, at block 706,the computer device may receive an action input from the user.Furthermore, at block 708, the computer device may cause the display ofan action of the at least a portion of the virtual body part based onthe action input. In an additional aspect, the action may be physicallynon-corresponding to the action input. Furthermore, the selection inputand action input may be at least a part of pre-training a user.

Turning to FIG. 8, an example methodology 800 is presented forpresenting a controllable virtual body part to a user. In an aspect, atblock 802, a computer device may provide a virtual body part to a uservia a display device. Furthermore, at block 804, the computer device mayreceive a selection input and an action input from the user. In someaspects, the selection input and the action input may be associated withat least a portion of the virtual image, which may include a virtualbody part. Furthermore, the selection input and action input may be atleast a part of pre-training a user. Additionally, at block 806,methodology 800 may include instantiating virtual movement of thevirtual image. In an aspect, block 806 may be, in a non-limiting aspect,performed by a computer device or by the user. Furthermore, at block808, the methodology 800 may include reinitiating neurologicalfunctionality based on the instantiating. In an aspect, block 808 maybe, in a non-limiting aspect, performed by a computer device or by theuser.

Referring to FIG. 9, an example system 900 is displayed for creating aUCI. For example, system 900 can reside at least partially within one ormore computing or processing devices. It is to be appreciated thatsystem 900 is represented as including functional blocks, which can befunctional blocks that represent processes implemented by a processor,software, or combination thereof (e.g., firmware). System 900 includes alogical grouping 902 of electrical components that can act inconjunction. For instance, logical grouping 902 can include anelectrical component 904 for obtaining anatomical and physiological dataassociated with a body. In an aspect, electrical component 904 maycomprise anatomical and physiological data obtaining component 302 (FIG.3). In addition, logical grouping 902 can include an electricalcomponent 906 for storing the anatomical and physiological data in adatabase. In an aspect, electrical component 906 may comprise UCIcreating device 300, memory 304 (FIG. 3), or processor 402 (FIG. 4). Inaddition, logical grouping 902 can include an electrical component 908for creating a UCI based on the stored anatomical and physiologicaldata. In an aspect, electrical component 908 may comprise UCI creatingcomponent 310 (FIG. 3).

Additionally, system 900 can include a memory 910 that retainsinstructions for executing processes associated with the electricalcomponents 904, 906, and 908, stores data used or obtained by theelectrical components 904, 906, and 908, etc. While shown as beingexternal to memory 910, it is to be understood that one or more of theelectrical components 904, 906, and 908 can exist within memory 910. Inone example, electrical components 904, 906, and 908 can comprise atleast one processor, or each electrical component 904, 906, and 908 canbe a corresponding module of at least one processor. Moreover, in anadditional or alternative example, electrical components 904, 906, and908 can be a computer program product including a computer readablemedium, where each electrical component 904, 906, and 908 can becorresponding code.

Referring to FIG. 10, an example system 1000 is displayed for creating aUCI. For example, system 1000 can reside at least partially within oneor more computing or processing devices. It is to be appreciated thatsystem 1000 is represented as including functional blocks, which can befunctional blocks that represent processes implemented by a processor,software, or combination thereof (e.g., firmware). System 1000 includesa logical grouping 1002 of electrical components that can act inconjunction. For instance, logical grouping 1002 can include anelectrical component 1004 for obtaining at least one default parameterassociated with a UCI. In an aspect, electrical component 1004 maycomprise computer device 102 (FIGS. 1 and 2). In addition, logicalgrouping 1002 can include an electrical component 1006 for obtaining atleast one user parameter associated with a user body. In an aspect,electrical component 1006 may comprise computer device 102 (FIGS. 1 and2). In addition, logical grouping 1002 can include electrical component1008 for comparing the at least one default parameter and the at leastone user parameter. In an aspect, electrical component 808 may compriseuser-configured UCI manager 212 (FIG. 2). In addition, logical grouping1002 can include an electrical component 1010 for constructing auser-configured UCI by adjusting one or more of the at least one defaultparameter. In an aspect, electrical component 1010 may compriseuser-configured UCI manager 212 (FIG. 2). In addition, logical grouping1002 can include an electrical component 1012 for providing theuser-configured UCI to the user for pre-action training. In an aspect,electrical component 1012 may comprise computer device 102 (FIGS. 1 and2).

Additionally, system 1000 can include a memory 1010 that retainsinstructions for executing processes associated with the electricalcomponents 1004, 1006, 1008, 1010, and 1012, stores data used orobtained by the electrical components 1004, 1006, 1008, 1010, and 1012,etc. While shown as being external to memory 1010, it is to beunderstood that one or more of the electrical components 1004, 1006,1008, 1010, and 1012 can exist within memory 1010. In one example,electrical components 1004, 1006, 1008, 1010, and 1012 can comprise atleast one processor, or each electrical component 1004, 1006, 1008,1010, and 1012 can be a corresponding module of at least one processor.Moreover, in an additional or alternative example, electrical components1004, 1006, 1008, 1010, and 1012 can be a computer program productincluding a computer readable medium, where each electrical component1004, 1006, 1008, 1010, and 1012 can be corresponding code.

Referring to FIG. 11, an example system 1100 is displayed for creating aUCI. For example, system 1100 can reside at least partially within oneor more computing or processing devices. It is to be appreciated thatsystem 1100 is represented as including functional blocks, which can befunctional blocks that represent processes implemented by a processor,software, or combination thereof (e.g., firmware). System 1100 includesa logical grouping 1102 of electrical components that can act inconjunction. For instance, logical grouping 1102 can include anelectrical component 1104 for providing a virtual body part to a user.In an aspect, electrical component 1104 may comprise computer device 102(FIGS. 1 and 2). In addition, logical grouping 1102 can include anelectrical component 1106 for receiving a selection input from the userassociated with at least a portion of the virtual body part. In anaspect, electrical component 1106 may selection input manager 206 (FIG.2). In addition, logical grouping 1102 can include an electricalcomponent 1108 for receiving an action input from the user. In anaspect, electrical component 1108 may comprise action input manager 208(FIG. 2). In addition, logical grouping 1102 can include an electricalcomponent 1110 for displaying a action of the portion of the virtualbody part based on the action input. In an aspect, electrical component1110 may comprise computer device 102 (FIGS. 1 and 2).

Additionally, system 1100 can include a memory 1110 that retainsinstructions for executing processes associated with the electricalcomponents 1104, 1106, 1108, and 1110, stores data used or obtained bythe electrical components 1104, 1106, 1108, and 1110, etc. While shownas being external to memory 1110, it is to be understood that one ormore of the electrical components 1104, 1106, 1108, and 1110 can existwithin memory 1110. In one example, electrical components 1104, 1106,1108, and 1110 can comprise at least one processor, or each electricalcomponent 1104, 1106, 1108, and 1110 can be a corresponding module of atleast one processor. Moreover, in an additional or alternative example,electrical components 1104, 1106, 1108, and 1110 can be a computerprogram product including a computer readable medium, where eachelectrical component 1104, 1106, 1108, and 1110 can be correspondingcode.

Referring to FIG. 12, an example system 1200 is displayed forinstantiating virtual movement of a virtual image and reinitiatingneurological functionality. For example, system 1200 can reside at leastpartially within one or more computing or processing devices. It is tobe appreciated that system 1200 is represented as including functionalblocks, which can be functional blocks that represent processesimplemented by a processor, software, or combination thereof (e.g.,firmware). System 1200 includes a logical grouping 1202 of electricalcomponents that can act in conjunction. For instance, logical grouping1202 can include an electrical component 1204 for providing a virtualimage to a user via a display device. In addition, logical grouping 1202can include an electrical component 1206 for receiving a selection inputand an action input from the user. In addition, logical grouping 1202can include an electrical component 1208 for instantiating virtualmovement of the virtual image. In addition, logical grouping 1202 caninclude an electrical component 1210 for reinitiating neurologicalfunctionality based on the instantiating. In an aspect, system 1200 maycomprise computer device 102 (FIGS. 1 and 2).

Additionally, system 1200 can include a memory 1212 that retainsinstructions for executing processes associated with the electricalcomponents 1204, 1206, 1208, and 1210, stores data used or obtained bythe electrical components 1204, 1206, 1208, and 1210, etc. While shownas being external to memory 1212, it is to be understood that one ormore of the electrical components 1204, 1206, 1208, and 1210 can existwithin memory 1212. In one example, electrical components 1204, 1206,1208, and 1210 can comprise at least one processor, or each electricalcomponent 1204, 1206, 1208, and 1210 can be a corresponding module of atleast one processor. Moreover, in an additional or alternative example,electrical components 1204, 1206, 1208, and 1210 can be a computerprogram product including a computer readable medium, where eachelectrical component 1204, 1206, 1208, and 1210 can be correspondingcode.

FIG. 13 is a representative drawing of a system 1300, which may includea non-virtual robot 1301, which may be configured to move in response toan input from a user. In an aspect, such input may be anon-corresponding movement input by an input device, such as a mouse, ina manner according to one or more methods provided herein. In an aspect,non-virtual robot 1301 may comprise a prosthesis, exoskeleton, or othermotorized device that may physically move in response to one or moreinputs or pre-programmed or pre-recoded controls.

Additionally, non-virtual robot 1301 may include a motor 1302, which maybe a uni- or bi-directional motor for moving one or more moveablesubstructures 1308, which may comprise one or more parts of non-virtualrobot 1301, such as, but not limited to a finger, limb, head, foot,hand, etc. Some actuator technologies or body part designs may utilize aplurality of motors 1302 (or other actuators) to move the one or moremoveable substructures 1308. Further, to create such movement,non-virtual robot 1301 may include a clutch 1304 and/or a gearbox 1306for controlling aspects of the movement of moveable substructure 1308,such as, but not limited to, speed, force, etc.

Furthermore, system 1300 may include a controller 1312, which may beconfigured to control motor 1302 and/or any other component ofnon-virtual robot 1301 based on one or more inputs. In an aspect, theseone or more inputs may comprise non-corresponding input from a userand/or a feedback input output by one or more sensors 1310, which may beconfigured to sense and/or analyze movement of the one or more moveablesubstructure 1308.

FIG. 14 is a representative wiring diagram of a device 1400, which maycomprise a non-virtual robot, prosthesis, or exoskeleton body part, suchas, but not limited to, non-virtual robot 1301 of FIG. 13. In an aspect,device 1400 may utilize a manual switch 1406 to engage either of thebi-directional circuits 1404 for controlling a motor 1402, which may bea bi-directional motor. In an aspect, manual switch 1406 may be athree-position Double Pole Double Throw (2P2T) switch for engagingeither open or close operation, and which may be center-loaded forneither engagement. Furthermore, device 1400 may include a pair (or morethan two) of limit switches 1404 corresponding to two (or more)interleaved circuits (extensor and flexor, i.e. open and close), whichmay limit motion associated with motor 1402.

FIG. 15 is a representative wiring diagram of a device 1500, which maybe a non-virtual robot, prosthesis, or exoskeleton body part (e.g. ofFIGS. 13 and/or 14). In an aspect, device 1500 may operate in responseto one or more digital outputs 1508 from a computing device 1510, whichmay control the movement of device 1500 and the associated motor 1502.For example, the digital outputs 1508 may engage bi-directionalcircuits, which may incorporate the 2P2T switch circuits present in FIG.14 (not shown here). Furthermore, current amplifiers 1506 (or voltageamplifiers) may amplify the one or more digital outputs 1508 (or analogoutputs) to cause movement via motor 1502. Also, though not shown inFIG. 15, device 1500 may include a plurality of sensors capable of beingincorporated which each of one or more body part structures orsub-structures (e.g. moveable substructure 1308 of FIG. 13).

FIG. 16 is a block diagram illustrating a machine in the example form ofa computer system 1600, within which a set or sequence of instructionsfor causing the machine to perform any one of the methodologiesdiscussed herein may be executed, according to an example embodiment. Inalternative embodiments, the machine operates as a standalone device ormay be connected (e.g. networked) to other machines. In a networkeddeployment, the machine may operate in the capacity of either a serveror a client machine in server-client network environments, or it may actas a peer machine in peer-to-peer (or distributed) network environments.The machine may be a personal computer (PC), a tablet PC, a set-top box(STB), a Personal Digital Assistant (PDA), a mobile telephone, a webappliance, a network router, switch or bridge, a cloud-based computingdevice, or any machine capable of executing instructions (sequential orotherwise) that specify actions to be taken by that machine. Further,while only a single machine is illustrated, the term “machine” shallalso be taken to include any collection of machines that individually orjointly execute a set (or multiple sets) of instructions to perform anyone or more of the methodologies discussed herein.

Example computer system 1600 includes at least one processor 1602 (e.g.a central processing unit (CPU), a graphics processing unit (GPU) orboth, processor cores, compute nodes, etc.), a main memory 1604 and astatic memory 1605, which communicate with each other via a link 1608(e.g. bus). The computer system 1600 may further include a video displayunit 1610, an alphanumeric input device 1612 (e.g. a keyboard), and auser interface (UI) navigation device 1614 (e.g. a mouse). In oneembodiment, the video display unit 1610, input device 1612 and UInavigation device 1614 are incorporated into a touch screen display. Thecomputer system 1600 may additionally include a storage device 1615(e.g. a drive unit), a signal generation device 1618 (e.g. a speaker), anetwork interface device 1620, and one or more sensors (not shown), suchas a global positioning system (GPS) sensor, compass, accelerometer, orother sensor.

The storage device 1615 includes a machine-readable medium 1622 on whichis stored one or more sets of data structures and instructions 1624(e.g. software) embodying or utilized by any one or more of themethodologies or functions described herein. The instructions 1624 mayalso reside, completely or at least partially, within the main memory1604, static memory 1605, and/or within the processor 1602 duringexecution thereof by the computer system 1600, with the main memory1604, static memory 1605, and the processor 1602 also constitutingmachine-readable media.

While the machine-readable medium 1622 is illustrated in an exampleembodiment to be a single medium, the term “machine-readable medium” mayinclude a single medium or multiple media (e.g. a centralized ordistributed database, and/or associated caches and servers) that storethe one or more instructions 1624. The term “machine-readable medium”shall also be taken to include any tangible medium that is capable ofstoring, encoding or carrying instructions for execution by the machineand that cause the machine to perform any one or more of themethodologies of the present disclosure or that is capable of storing,encoding or carrying data structures utilized by or associated with suchinstructions. The term “machine-readable medium” shall accordingly betaken to include, but not be limited to, solid-state memories, andoptical and magnetic media. Specific examples of machine-readable mediainclude non-volatile memory, including, by way of example, semiconductormemory devices (e.g. Electrically Programmable Read-Only Memory (EPROM),Electrically Erasable Programmable Read-Only Memory (EEPROM)) and flashmemory devices; magnetic disks such as internal hard disks and removabledisks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

The instructions 1624 may further be transmitted or received over acommunications network 1626 using a transmission medium via the networkinterface device 1620 utilizing any one of a number of well-knowntransfer protocols (e.g. HTTP, XML). Examples of communication networksinclude a local area network (LAN), a wide area network (WAN), theInternet, mobile telephone networks, Plain Old Telephone (POTS)networks, and wireless data networks (e.g. Wi-Fi, 3G, and 4G LTE/LTE-Aor WiMAX networks). The term “transmission medium” shall be taken toinclude any intangible medium that is capable of storing, encoding, orcarrying instructions for execution by the machine, and includes digitalor analog communications signals or other intangible medium tofacilitate communication of such software.

Examples, as described herein, may include, or may operate on, logic ora number of modules, modules, or mechanisms. Modules are tangibleentities capable of performing specified operations and may beconfigured or arranged in a certain manner. In an example, circuits maybe arranged (e.g. internally or with respect to external entities suchas other circuits) in a specified manner as a module. In an example, thewhole or part of one or more computer systems (e.g. a standalone, clientor server computer system) or one or more hardware processors may beconfigured by firmware or software (e.g. instructions, an applicationportion, or an application) as a module that operates to performspecified operations. In an example, the software may reside (1) on anon-transitory machine-readable medium or (2) in a transmission signal.In an example, the software, when executed by the underlying hardware ofthe module, causes the hardware to perform the specified operations.

Accordingly, the terms “module” and “module” are understood to encompassa tangible entity, be that an entity that is physically constructed,specifically configured (e.g. hardwired), or temporarily (e.g.transitorily) configured (e.g. programmed) to operate in a specifiedmanner or to perform part or all of any operation described herein.Considering examples in which modules are temporarily configured, oneinstantiation of a module may not exist simultaneously with anotherinstantiation of the same or different module. For example, where themodules comprise a general-purpose hardware processor configured usingsoftware, the general-purpose hardware processor may be configured asrespective different modules at different times. Accordingly, softwaremay configure a hardware processor, for example, to constitute aparticular module at one instance of time and to constitute a differentmodule at a different instance of time.

Additional examples of the presently described method, system, anddevice embodiments include the following, non-limiting configurations.Each of the following non-limiting examples may stand on its own, or maybe combined in any permutation or combination with any one or more ofthe other examples provided below or throughout the present disclosure.The preceding description and the drawings sufficiently illustratespecific embodiments to enable those skilled in the art to practicethem. Other embodiments may incorporate structural, logical, electrical,process, and other changes. Portions and features of some embodimentsmay be included in, or substituted for, those of other embodiments.

As used in this disclosure, the terms “component,” “module,” “system”and the like are intended to include a computer-related entity, such asbut not limited to hardware, firmware, a combination of hardware andsoftware, software, or software in execution. For example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration, both an application runningon a computing device and the computing device can be a component. Oneor more components can reside within a process and/or thread ofexecution and a component may be localized on one computer and/ordistributed between two or more computers. In addition, these componentscan execute from various computer readable media having various datastructures stored thereon. The components may communicate by way oflocal and/or remote processes such as in accordance with a signal havingone or more data packets, such as data from one component interactingwith another component in a local system, distributed system, and/oracross a network such as the Internet with other systems by way of thesignal.

Moreover, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom the context, the phrase “X employs A or B” is intended to mean anyof the natural inclusive permutations. That is, the phrase “X employs Aor B” is satisfied by any of the following instances: X employs A; Xemploys B; or X employs both A and B. In addition, the articles “a” and“an” as used in this disclosure and the appended claims should generallybe construed to mean “one or more” unless specified otherwise or clearfrom the context to be directed to a singular form.

Various aspects or features will be presented in terms of systems thatmay include a number of devices, components, modules, and the like. Itis to be understood and appreciated that the various systems may includeadditional devices, components, modules, etc. and/or may not include allof the devices, components, modules etc. discussed in connection withthe figures. A combination of these approaches may also be used.

The various illustrative logics, logical blocks, modules, and circuitsdescribed in connection with the embodiments disclosed herein may beimplemented or performed with a general purpose processor, a digitalsignal processor (DSP), an application specific integrated circuit(ASIC), a field programmable gate array (FPGA) or other programmablelogic device, discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the processesdescribed herein. A general-purpose processor may be a microprocessor,but, in the alternative, the processor may be any conventionalprocessor, controller, microcontroller, or state machine. A processormay also be implemented as a combination of computing devices, e.g., acombination of a DSP and a microprocessor, a plurality ofmicroprocessors, one or more microprocessors in conjunction with a DSPcore, or any other such configuration. Additionally, at least oneprocessor may comprise one or more modules operable to perform one ormore of the steps and/or actions described above.

Further, the steps and/or actions of a method or algorithm described inconnection with the aspects disclosed herein may be embodied directly inhardware, in a software module executed by a processor, or in acombination of the two. A software module may reside in RAM memory,flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a harddisk, a removable disk, a CD-ROM, or any other form of storage mediumknown in the art. An exemplary storage medium may be coupled to theprocessor, such that the processor can read information from, and writeinformation to, the storage medium. In the alternative, the storagemedium may be integral to the processor. Further, in some aspects, theprocessor and the storage medium may reside in an ASIC. Additionally,the ASIC may reside in a user terminal. In the alternative, theprocessor and the storage medium may reside as discrete components in auser terminal. Additionally, in some aspects, the steps and/or actionsof a method or algorithm may reside as one or any combination or set ofcodes and/or instructions on a machine readable medium and/or computerreadable medium, which may be incorporated into a computer programproduct.

In one or more aspects, the processes described may be implemented inhardware, software, firmware, or any combination thereof. If implementedin software, the processes may be stored or transmitted as one or moreinstructions or code on a computer-readable medium. Computer-readablemedia includes both computer storage media and communication mediaincluding any medium that facilitates transfer of a computer programfrom one place to another. A storage medium may be any available mediathat can be accessed by a computer. By way of example, and notlimitation, such computer-readable media can comprise RAM, ROM, EEPROM,CD-ROM or other optical disk storage, magnetic disk storage or othermagnetic storage devices, or any other medium that can be used to carryor store desired program code in the form of instructions or datastructures and that can be accessed by a computer. Also, any connectionmay be termed a computer-readable medium. For example, if software istransmitted from a website, server, or other remote source using acoaxial cable, fiber optic cable, twisted pair, digital subscriber line(DSL), or wireless technologies such as infrared, radio, and microwave,then the coaxial cable, fiber optic cable, twisted pair, DSL, orwireless technologies such as infrared, radio, and microwave areincluded in the definition of medium. Disk and disc, as used herein,includes compact disc (CD), laser disc, optical disc, digital versatiledisc (DVD), floppy disk and blu-ray disc where disks usually reproducedata magnetically, while discs usually reproduce data optically withlasers. Combinations of the above should also be included within thescope of computer-readable media.

While the foregoing disclosure discusses illustrative aspects and/orembodiments, it should be noted that various changes and modificationscould be made herein without departing from the scope of the describedaspects and/or embodiments as defined by the appended claims.Furthermore, although elements of the described aspects and/orembodiments may be described or claimed in the singular, the plural iscontemplated unless limitation to the singular is explicitly stated.Additionally, all or a portion of any aspect and/or embodiment may beutilized with all or a portion of any other aspect and/or embodiment,unless stated otherwise.

What is claimed is:
 1. A method of constructing a user-controllableimage, comprising: obtaining anatomical and physiological dataassociated with a body; storing the anatomical and physiological data ina database; and creating the user-controllable image based on the storedanatomical and physiological data, wherein the user-controllable imageis configurable to a user, wherein at least a moveable portion of theuser-controllable image is constructed to move based on input from auser, and wherein the user-controllable image is constructed so as toenable pre-action training the user.
 2. The method of claim 1, whereinthe anatomical and physiological data comprises parameters associatedwith a plurality of one or more bones, one or more muscles, and one ormore tendons.
 3. The method of claim 1, wherein the anatomical andphysiological data comprises parameters associated with skin.
 4. Themethod of claim 1, wherein the user-controllable image comprises anadjacent portion of the user-controllable image adjacent to the moveableportion of the user-controllable image, and wherein the adjacent portionis configured to move as a result of the moveable portion moving.
 5. Themethod of claim 1, wherein the anatomical and physiological data isobtained via a motion capture device.
 6. The method of claim 1, furthercomprising: obtaining at least one default parameter associated with theuser-controllable image; obtaining at least one user parameterassociated with a user body; comparing the at least one defaultparameter and the at least one user parameter; configuring theuser-configured user-controllable image by adjusting one or more of theat least one default parameter where the at least one user parameterdiffers from the at least one default parameter.
 7. A method ofcontrolling a user-controllable image, comprising: providing a virtualbody part to a user, wherein the user-controllable image comprises thevirtual body part; receiving a selection input from the user, whereinthe selection input is associated with at least a portion of the virtualbody part; receiving an action input from the user; and displaying anaction of the at least a portion of the virtual body part based on theaction input, wherein the action is physically non-corresponding to theaction input and wherein the selection input and action input are atleast a part of pre-action training a user.
 8. The method of claim 7,wherein the at least a part of pre-action training a user comprises apre-action exercise game.
 9. The method of claim 7, further comprisingmeasuring one or more of a neurological, skeletomuscular, or biochemicalresponse of the user based on the action input.
 10. The method of claim9, wherein the measuring utilizes one or more imaging technologies. 11.The method of claim 9, further comprising: comparing the neurologicalresponse to a stored neurological characteristic value to obtain aresponse comparison; and altering one or more subsequent pre-actiontraining activities based on the response comparison.
 12. The method ofclaim 11, wherein the stored neurological characteristic value isobtained by measuring one or more baseline neurological characteristics.13. The method of claim 11, wherein the stored neurologicalcharacteristic value is obtained from one or more previously measuredneurological responses.
 14. The method of claim 9, further comprising:comparing the neurological response to a stored response to obtain aresponse comparison; and diagnosing a medical condition based on theresponse comparison.
 15. The method of claim 7, wherein the actioncomprises a measurement of action based on the action input, the methodfurther comprising: displaying the measurement of action to the user.16. The method of claim 7, wherein displaying the action comprises:transmitting a control signal based on one or more of the selectioninput and the action input to at least one non-virtual external bodypart device; and causing the at least one non-virtual external body partdevice to move based on the control signal.
 17. The method of claim 16,wherein the at least one non-virtual external body part device isaffixed to the user.
 18. The method of claim 7, wherein displaying theaction comprises: transmitting a control signal based on one or more ofthe selection input and the action input to a feedback device; andcausing the feedback device to provide feedback to the user based on thecontrol signal.
 19. The method of claim 7, further comprising displayinga demonstrative action of the virtual body part to the user.
 20. Themethod of claim 19, wherein the input comprises an attempt by the userto mimic the demonstrative action.
 21. The method of claim 19, whereinthe input comprises an attempt by the user to interact with thedemonstrative action.
 22. The method of claim 19, wherein thedemonstrative action is displayed as a ghost action.
 23. A method ofcognitive rehabilitation, comprising: providing a virtual image to auser via a display device; receiving selection input and action inputfrom the user; instantiating virtual movement of the virtual image; andreinitiating neurological functionality based on the instantiating. 24.The method of claim 23, wherein reinitiating neurological functionalitycomprises creating at least one neurological engagement associated withone or more portions of a nervous system, wherein the at least oneneurological engagement is not an initial vehicle of the neurologicalfunctionality.
 25. The method of claim 23, wherein the neurologicalfunctionality was previously made dysfunctional.